ai-video-atlas

endpoint

https://mcp.aivideoatlas.com/mcp

protocol

streamable-http ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing · is it yours? claim it

karma

0 · newcomer

Is ai-video-atlas live?

Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.

Is ai-video-atlas free to use?

Yes — the hub reached it with no key and no payment.

What tools does ai-video-atlas have?

8 tools: plan_shots, find_shot, best_prompt, recommend_model, get_prices, get_guide, get_workflow, whats_new.

Is ai-video-atlas safe to connect?

The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• get_guide open 1h ago

  Prompting guidance from AI Video Atlas, sourced from vendor prompting docs (Google, BytePlus, Runway, Luma, MiniMax, Alibaba, LTX, xAI, fal) plus proven Atlas examples. Pass model (kling, veo, seedance, runway, luma, hailuo, wan, ltx, grok-imagine…) for prompt structure, camera language, what the model responds to, things to avoid and known limits; or topic (shot-vocabulary, tagging, consistent-characters, i2v-vs-r2v, setup-playbooks). Every item carries its source URL; items marked atlas-editorial are our summary, not a vendor claim. Call with no arguments to list what exists. Use before writing a prompt for a specific model.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "kind": {
        "enum": [
          "structure",
          "camera",
          "responds_to",
          "mode",
          "consistency",
          "tagging",
          "audio",
          "avoid",
          "limits",
          "workflow",
          "technique",
          "pricing"
        ],
        "type": "string",
        "description": "Optional filter, e.g. camera or avoid"
      },
      "model": {
        "type": "string",
        "description": "Model family, e.g. kling, veo, seedance, runway, luma, hailuo, wan, ltx, grok-imagine"
      },
      "topic": {
        "enum": [
          "consistent-characters",
          "i2v-vs-r2v",
          "setup-playbooks",
          "shot-vocabulary",
          "tagging"
        ],
        "type": "string"
      }
    }
  }

  arguments 37 lines copy
• get_workflow open 1h ago

  How-to workflows, tools and model guides for AI video, grouped by job: consistent-character (Keep a character consistent), lip-sync (Lip sync & talking heads), product-ad (Product ads & UGC), camera (Direct the camera), long (Longer & multi-shot videos), i2v (Animate a still image), edit (Edit or restyle footage), upscale (Upscale & smooth), local (Run it on your own GPU), models (Models & hosts). Pass job for a curated list, query for free text (e.g. "comfyui lipsync", "upscale to 4k"), or slug for one item in full. Returns sources, creators, license and price as stated.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "job": {
        "enum": [
          "consistent-character",
          "lip-sync",
          "product-ad",
          "camera",
          "long",
          "i2v",
          "edit",
          "upscale",
          "local",
          "models"
        ],
        "type": "string"
      },
      "slug": {
        "type": "string"
      },
      "limit": {
        "type": "integer",
        "default": 8,
        "maximum": 25
      },
      "query": {
        "type": "string"
      }
    }
  }

  arguments 31 lines copy
• whats_new open 1h ago

  What is new in AI Video Atlas: the newest sourced shots and guides added in the last N days (default 7), newest first, with X like counts where we have them ("new" otherwise). Use for "what's new in AI video", weekly roundups, or trend questions. For the full weekly digest (new models, price changes, new shots, legacy prices) read https://aivideoatlas.com/digest/latest.json.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "days": {
        "type": "integer",
        "default": 7,
        "maximum": 60
      },
      "kind": {
        "enum": [
          "shots",
          "guides",
          "all"
        ],
        "type": "string",
        "default": "all"
      },
      "limit": {
        "type": "integer",
        "default": 10,
        "maximum": 30
      }
    }
  }

  arguments 24 lines copy
• plan_shots unknown never probed

  Plan a multi-shot AI video from a plain description (deterministic, built only from Atlas data; no AI generation). Output is staged: decide (model/mode/clip length/aspect/cost with reasons and capability checks), direct (shot list with per-model prompts), assets (every reference/frame with status needs-generation|user-supplied|approved), image_prompts, and steps, which include a STOP: get the user to approve assets before generating any video. Global directives (same X in every shot, vertical, no text, style) apply to all shots; questions and request wording are never planned as shots; an explicit shot count is honored; clips longer than an endpoint's documented max are split. The description is split into beats (sentences, clauses, and cues like "then", "cut to", "close-up", "wide"). For each beat it returns a shot type; a recommended model endpoint with its current vendor-stated $/s and source; the generation mode to use (t2v, i2v, reference-to-video, start/end frame, v2v, lip sync; only modes the vendor docs confirm) with a one-line reason; image prompts for any input frames, plus a shared character/product reference sheet when shots must match; an adapted prompt built from the best-matching sourced example (credited and linked), an estimated cost (5 s per shot by default), and a how-to workflow when one applies (lip sync, consistent character…). It also returns a total. budget_usd (total) and/or max_per_shot steer it to cheaper supported endpoints; each shot also offers a cheaper alternative with its cost, and the plan says if the budget can't be met. Use this for "plan / storyboard / make me a video of…" requests; use find_shot for a single shot. Before presenting, adapt the wording to the user's voice, context and brand (names, tone, product details), but keep the prices, models, modes, clip lengths and reference tags exactly as returned.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "description"
    ],
    "properties": {
      "style": {
        "type": "string",
        "description": "Optional look applied to every shot, e.g. \"35mm film, warm grade\" or \"anime\"."
      },
      "budget_usd": {
        "type": "number",
        "description": "Optional total budget in USD."
      },
      "force_plan": {
        "type": "boolean",
        "description": "Return a shot plan even when the request reads as a pricing-only question"
      },
      "description": {
        "type": "string",
        "description": "What the video should show, in plain words. Several beats are fine."
      },
      "clip_seconds": {
        "type": "number",
        "default": 5,
        "description": "Seconds per shot (default 5)."
      },
      "max_per_shot": {
        "type": "number",
        "description": "Optional maximum USD per shot."
      }
    }
  }

  arguments 33 lines copy
• find_shot unknown never probed

  Search AI Video Atlas's library of 107 sourced AI video shots (real prompts that creators posted, with the model used, an estimated cost and a link to the original). Use this FIRST when the user describes a shot, scene, style or job ("product ad with a rotating can", "anime fight", "lip sync dialogue", "drone over mountains"). Filters: shot_type (ads, music, shorts, characters, product, cinematic, lipsync, anime), model (e.g. kling, veo, seedance), max_cost_usd (estimated cost of the clip; when the prompt states no length we use a 5-second clip). Returns prompt excerpts; call best_prompt with a slug for the full prompt. Do not use for prices alone (use get_prices) or for tools/workflows (use get_workflow).

  mcp-tool

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  {
    "type": "object",
    "required": [
      "query"
    ],
    "properties": {
      "limit": {
        "type": "integer",
        "default": 5,
        "maximum": 20,
        "minimum": 1
      },
      "model": {
        "type": "string",
        "description": "Only shots made with this model family (strict; comparisons that merely include it are excluded), e.g. kling, veo, seedance, hailuo, runway, luma, wan, ltx, sora"
      },
      "query": {
        "type": "string",
        "description": "What the shot should look like or achieve, in plain words."
      },
      "shot_type": {
        "enum": [
          "ads",
          "music",
          "shorts",
          "characters",
          "product",
          "cinematic",
          "lipsync",
          "anime"
        ],
        "type": "string"
      },
      "max_cost_usd": {
        "type": "number",
        "description": "Max estimated cost per clip in USD"
      }
    }
  }

  arguments 39 lines copy
• best_prompt unknown never probed

  Get the full, sourced prompt that best matches a shot (free text or a slug from find_shot), optionally for a target model. Returns the exact prompt text as the creator posted it, the creator credit and source, the model it was made with, and factual adaptation notes when the target model differs (other Atlas shots on the target model and its current supported price). Atlas never claims how a prompt will perform on a model it was not made with; treat adaptation notes as guidance.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "shot"
    ],
    "properties": {
      "shot": {
        "type": "string",
        "description": "A slug from find_shot or a plain description of the shot."
      },
      "model": {
        "type": "string",
        "description": "Target model family (optional)."
      }
    }
  }

  arguments 16 lines copy
• recommend_model unknown never probed

  Recommend which AI video model to use for a shot, with the evidence: how many sourced Atlas shots of that kind were made with each model, the cheapest supported vendor-stated $/s, and an estimated total for the clip length and number of clips. Pass budget_usd (total) and/or max_per_shot to drop models whose estimate exceeds it; over-budget models are listed with their cost. Each row includes the generation modes the vendor docs confirm (t2v, i2v, reference-to-video, start/end, v2v, lip sync; unknown where docs do not say). Legacy, deprecated and discontinued models are never recommended. Filters by the required mode FIRST (detected from the shot text or the mode argument; endpoints whose docs say unknown are excluded), then ranks the cheapest qualifying endpoint first and notes when a pricier one has more proof. Includes each endpoint's max clip length and splits long clips.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "shot"
    ],
    "properties": {
      "mode": {
        "enum": [
          "t2v",
          "i2v",
          "r2v",
          "start_end",
          "v2v",
          "lipsync"
        ],
        "type": "string",
        "description": "Required generation mode; detected from the shot text when omitted"
      },
      "shot": {
        "type": "string"
      },
      "clips": {
        "type": "integer",
        "default": 1
      },
      "budget_usd": {
        "type": "number",
        "description": "Total budget for all clips"
      },
      "clip_seconds": {
        "type": "number",
        "default": 5
      },
      "max_per_shot": {
        "type": "number",
        "description": "Max USD per clip"
      }
    }
  }

  arguments 39 lines copy
• get_prices unknown never probed

  Vendor-stated AI video prices per second from AI Video Atlas's tracker, each with its source URL and the date we checked it. Filter by model family or host. Legacy, deprecated and discontinued rows are excluded unless include_legacy=true (then they are flagged by status). Use for "how much does X cost", "cheapest model", or before quoting any cost.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "host": {
        "type": "string"
      },
      "sort": {
        "enum": [
          "cheapest",
          "model"
        ],
        "type": "string",
        "default": "cheapest"
      },
      "model": {
        "type": "string"
      },
      "include_legacy": {
        "type": "boolean",
        "default": false
      }
    }
  }

  arguments 23 lines copy

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.